Overview

Dataset statistics

Number of variables14
Number of observations840
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory92.0 KiB
Average record size in memory112.2 B

Variable types

Numeric13
Categorical1

Alerts

Año is highly overall correlated with 20 - 30 Mbps and 2 other fieldsHigh correlation
1 - 6 Mbps is highly overall correlated with Total and 1 other fieldsHigh correlation
6 - 10 Mbps is highly overall correlated with 10 - 20 Mbps and 4 other fieldsHigh correlation
10 - 20 Mbps is highly overall correlated with 6 - 10 Mbps and 4 other fieldsHigh correlation
20 - 30 Mbps is highly overall correlated with Año and 6 other fieldsHigh correlation
>=30 Mbps is highly overall correlated with Año and 6 other fieldsHigh correlation
Otros is highly overall correlated with Año and 2 other fieldsHigh correlation
Total is highly overall correlated with 1 - 6 Mbps and 5 other fieldsHigh correlation
Total2 is highly overall correlated with 1 - 6 Mbps and 5 other fieldsHigh correlation
id_Provincia has 35 (4.2%) zerosZeros
0.512 - 1 Mbps has 50 (6.0%) zerosZeros
6 - 10 Mbps has 38 (4.5%) zerosZeros
10 - 20 Mbps has 71 (8.5%) zerosZeros
20 - 30 Mbps has 104 (12.4%) zerosZeros
>=30 Mbps has 112 (13.3%) zerosZeros
Otros has 455 (54.2%) zerosZeros
Diferencia has 40 (4.8%) zerosZeros

Reproduction

Analysis started2023-07-16 22:58:17.072840
Analysis finished2023-07-16 22:58:39.907975
Duration22.84 seconds
Software versionydata-profiling vv4.3.1
Download configurationconfig.json

Variables

Año
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.8857
Minimum2014
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-07-16T19:58:39.963975image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12016
median2018
Q32020
95-th percentile2022
Maximum2022
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.528745
Coefficient of variation (CV)0.0012531656
Kurtosis-1.2039979
Mean2017.8857
Median Absolute Deviation (MAD)2
Skewness0.022512286
Sum1695024
Variance6.3945513
MonotonicityDecreasing
2023-07-16T19:58:40.076009image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2021 96
11.4%
2020 96
11.4%
2019 96
11.4%
2018 96
11.4%
2017 96
11.4%
2016 96
11.4%
2015 96
11.4%
2014 96
11.4%
2022 72
8.6%
ValueCountFrequency (%)
2014 96
11.4%
2015 96
11.4%
2016 96
11.4%
2017 96
11.4%
2018 96
11.4%
2019 96
11.4%
2020 96
11.4%
2021 96
11.4%
2022 72
8.6%
ValueCountFrequency (%)
2022 72
8.6%
2021 96
11.4%
2020 96
11.4%
2019 96
11.4%
2018 96
11.4%
2017 96
11.4%
2016 96
11.4%
2015 96
11.4%
2014 96
11.4%

Trimestre
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
3
216 
2
216 
1
216 
4
192 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters840
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 216
25.7%
2 216
25.7%
1 216
25.7%
4 192
22.9%

Length

2023-07-16T19:58:40.203028image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-16T19:58:40.360066image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
3 216
25.7%
2 216
25.7%
1 216
25.7%
4 192
22.9%

Most occurring characters

ValueCountFrequency (%)
3 216
25.7%
2 216
25.7%
1 216
25.7%
4 192
22.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 840
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 216
25.7%
2 216
25.7%
1 216
25.7%
4 192
22.9%

Most occurring scripts

ValueCountFrequency (%)
Common 840
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 216
25.7%
2 216
25.7%
1 216
25.7%
4 192
22.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 216
25.7%
2 216
25.7%
1 216
25.7%
4 192
22.9%

id_Provincia
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum0
Maximum23
Zeros35
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-07-16T19:58:40.479091image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15.75
median11.5
Q317.25
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation6.9263106
Coefficient of variation (CV)0.60228788
Kurtosis-1.2041954
Mean11.5
Median Absolute Deviation (MAD)6
Skewness0
Sum9660
Variance47.973778
MonotonicityNot monotonic
2023-07-16T19:58:40.618120image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 35
 
4.2%
1 35
 
4.2%
22 35
 
4.2%
21 35
 
4.2%
20 35
 
4.2%
19 35
 
4.2%
18 35
 
4.2%
17 35
 
4.2%
16 35
 
4.2%
15 35
 
4.2%
Other values (14) 490
58.3%
ValueCountFrequency (%)
0 35
4.2%
1 35
4.2%
2 35
4.2%
3 35
4.2%
4 35
4.2%
5 35
4.2%
6 35
4.2%
7 35
4.2%
8 35
4.2%
9 35
4.2%
ValueCountFrequency (%)
23 35
4.2%
22 35
4.2%
21 35
4.2%
20 35
4.2%
19 35
4.2%
18 35
4.2%
17 35
4.2%
16 35
4.2%
15 35
4.2%
14 35
4.2%

<0.512 mbps
Real number (ℝ)

Distinct371
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2898.4405
Minimum60
Maximum199768
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-07-16T19:58:40.748149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile90
Q1320
median1050
Q32565.75
95-th percentile7452.4
Maximum199768
Range199708
Interquartile range (IQR)2245.75

Descriptive statistics

Standard deviation10900.555
Coefficient of variation (CV)3.7608344
Kurtosis206.75317
Mean2898.4405
Median Absolute Deviation (MAD)850
Skewness13.299608
Sum2434690
Variance1.1882209 × 108
MonotonicityNot monotonic
2023-07-16T19:58:40.900193image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 20
 
2.4%
150 16
 
1.9%
180 16
 
1.9%
100 15
 
1.8%
160 15
 
1.8%
670 14
 
1.7%
710 12
 
1.4%
80 12
 
1.4%
260 11
 
1.3%
60 11
 
1.3%
Other values (361) 698
83.1%
ValueCountFrequency (%)
60 11
1.3%
70 3
 
0.4%
80 12
1.4%
90 20
2.4%
100 15
1.8%
101 3
 
0.4%
110 10
1.2%
111 8
 
1.0%
120 5
 
0.6%
130 1
 
0.1%
ValueCountFrequency (%)
199768 1
0.1%
162513 1
0.1%
134673 1
0.1%
38215 1
0.1%
37821 1
0.1%
37542 2
0.2%
37193 1
0.1%
37192 1
0.1%
36939 2
0.2%
33489 1
0.1%

0.512 - 1 Mbps
Real number (ℝ)

ZEROS 

Distinct633
Distinct (%)75.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10374.468
Minimum0
Maximum171244
Zeros50
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-07-16T19:58:41.216255image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11347
median3760.5
Q38328.25
95-th percentile51430.4
Maximum171244
Range171244
Interquartile range (IQR)6981.25

Descriptive statistics

Standard deviation21587.794
Coefficient of variation (CV)2.080858
Kurtosis17.521511
Mean10374.468
Median Absolute Deviation (MAD)2767.5
Skewness3.9664419
Sum8714553
Variance4.6603286 × 108
MonotonicityNot monotonic
2023-07-16T19:58:41.361297image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 50
 
6.0%
10 12
 
1.4%
40 10
 
1.2%
2850 8
 
1.0%
970 8
 
1.0%
1090 7
 
0.8%
3270 7
 
0.8%
9090 6
 
0.7%
1120 6
 
0.7%
400 5
 
0.6%
Other values (623) 721
85.8%
ValueCountFrequency (%)
0 50
6.0%
10 12
 
1.4%
14 1
 
0.1%
20 1
 
0.1%
30 2
 
0.2%
39 1
 
0.1%
40 10
 
1.2%
47 1
 
0.1%
50 3
 
0.4%
60 2
 
0.2%
ValueCountFrequency (%)
171244 1
0.1%
162274 1
0.1%
137189 1
0.1%
133385 1
0.1%
132937 1
0.1%
128187 1
0.1%
124468 1
0.1%
123589 1
0.1%
115197 1
0.1%
112593 1
0.1%

1 - 6 Mbps
Real number (ℝ)

HIGH CORRELATION 

Distinct831
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean150969.97
Minimum2842
Maximum2299705
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-07-16T19:58:41.509332image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2842
5-th percentile11900.4
Q128539.25
median48834.5
Q386897.5
95-th percentile727863.25
Maximum2299705
Range2296863
Interquartile range (IQR)58358.25

Descriptive statistics

Standard deviation348153.84
Coefficient of variation (CV)2.3061132
Kurtosis21.09886
Mean150969.97
Median Absolute Deviation (MAD)25713
Skewness4.4592125
Sum1.2681477 × 108
Variance1.2121109 × 1011
MonotonicityNot monotonic
2023-07-16T19:58:41.647352image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35409 3
 
0.4%
14014 3
 
0.4%
58588 2
 
0.2%
22409 2
 
0.2%
28600 2
 
0.2%
30727 2
 
0.2%
40285 2
 
0.2%
47454 1
 
0.1%
404645 1
 
0.1%
48995 1
 
0.1%
Other values (821) 821
97.7%
ValueCountFrequency (%)
2842 1
0.1%
3107 1
0.1%
3179 1
0.1%
3576 1
0.1%
3678 1
0.1%
4386 1
0.1%
5018 1
0.1%
5312 1
0.1%
5366 1
0.1%
6038 1
0.1%
ValueCountFrequency (%)
2299705 1
0.1%
2288772 1
0.1%
2281524 1
0.1%
2279875 1
0.1%
2267852 1
0.1%
2266948 1
0.1%
2253197 1
0.1%
2250898 1
0.1%
2250445 1
0.1%
2214760 1
0.1%

6 - 10 Mbps
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct757
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33783.187
Minimum0
Maximum403575
Zeros38
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-07-16T19:58:41.796383image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19.5
Q12967.75
median8303.5
Q329956
95-th percentile190929.05
Maximum403575
Range403575
Interquartile range (IQR)26988.25

Descriptive statistics

Standard deviation60759.295
Coefficient of variation (CV)1.7985069
Kurtosis9.7650201
Mean33783.187
Median Absolute Deviation (MAD)8143.5
Skewness3.0022283
Sum28377877
Variance3.6916919 × 109
MonotonicityNot monotonic
2023-07-16T19:58:41.940416image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38
 
4.5%
20 12
 
1.4%
110 4
 
0.5%
10 4
 
0.5%
6550 3
 
0.4%
150 3
 
0.4%
260 2
 
0.2%
26562 2
 
0.2%
1915 2
 
0.2%
7811 2
 
0.2%
Other values (747) 768
91.4%
ValueCountFrequency (%)
0 38
4.5%
10 4
 
0.5%
20 12
 
1.4%
30 1
 
0.1%
60 1
 
0.1%
65 1
 
0.1%
69 1
 
0.1%
70 1
 
0.1%
80 2
 
0.2%
90 2
 
0.2%
ValueCountFrequency (%)
403575 1
0.1%
402315 1
0.1%
335296 1
0.1%
331292 1
0.1%
321756 1
0.1%
311652 1
0.1%
311411 1
0.1%
307554 1
0.1%
299009 1
0.1%
297915 1
0.1%

10 - 20 Mbps
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct725
Distinct (%)86.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34638.142
Minimum0
Maximum886678
Zeros71
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-07-16T19:58:42.138462image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12039.5
median7766
Q324396.5
95-th percentile189469.1
Maximum886678
Range886678
Interquartile range (IQR)22357

Descriptive statistics

Standard deviation87389.352
Coefficient of variation (CV)2.5229226
Kurtosis33.883267
Mean34638.142
Median Absolute Deviation (MAD)7151
Skewness5.2130016
Sum29096039
Variance7.6368988 × 109
MonotonicityNot monotonic
2023-07-16T19:58:42.287501image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 71
 
8.5%
10 5
 
0.6%
50 4
 
0.5%
100 3
 
0.4%
1190 3
 
0.4%
1000 3
 
0.4%
1110 2
 
0.2%
21452 2
 
0.2%
3880 2
 
0.2%
5216 2
 
0.2%
Other values (715) 743
88.5%
ValueCountFrequency (%)
0 71
8.5%
10 5
 
0.6%
26 1
 
0.1%
30 1
 
0.1%
38 1
 
0.1%
40 2
 
0.2%
50 4
 
0.5%
70 1
 
0.1%
92 1
 
0.1%
100 3
 
0.4%
ValueCountFrequency (%)
886678 1
0.1%
816056 1
0.1%
712513 1
0.1%
676137 1
0.1%
577679 1
0.1%
576428 1
0.1%
573298 1
0.1%
487826 1
0.1%
467398 1
0.1%
445345 1
0.1%

20 - 30 Mbps
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct583
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19442.944
Minimum0
Maximum949093
Zeros104
Zeros (%)12.4%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-07-16T19:58:42.450529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1190
median2214.5
Q39284
95-th percentile75336.65
Maximum949093
Range949093
Interquartile range (IQR)9094

Descriptive statistics

Standard deviation70347.381
Coefficient of variation (CV)3.6181445
Kurtosis81.69084
Mean19442.944
Median Absolute Deviation (MAD)2214.5
Skewness8.0561923
Sum16332073
Variance4.948754 × 109
MonotonicityNot monotonic
2023-07-16T19:58:42.595566image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 104
 
12.4%
10 24
 
2.9%
50 18
 
2.1%
20 13
 
1.5%
30 8
 
1.0%
40 7
 
0.8%
220 5
 
0.6%
290 5
 
0.6%
130 4
 
0.5%
90 4
 
0.5%
Other values (573) 648
77.1%
ValueCountFrequency (%)
0 104
12.4%
10 24
 
2.9%
14 1
 
0.1%
20 13
 
1.5%
30 8
 
1.0%
40 7
 
0.8%
50 18
 
2.1%
53 1
 
0.1%
60 3
 
0.4%
67 1
 
0.1%
ValueCountFrequency (%)
949093 1
0.1%
897964 1
0.1%
576859 1
0.1%
536049 1
0.1%
502275 1
0.1%
483572 1
0.1%
480237 1
0.1%
437662 1
0.1%
365713 1
0.1%
296155 1
0.1%

>=30 Mbps
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct549
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79179.562
Minimum0
Maximum3618689
Zeros112
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-07-16T19:58:42.747598image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median882.5
Q319660.75
95-th percentile322176.4
Maximum3618689
Range3618689
Interquartile range (IQR)19653.75

Descriptive statistics

Standard deviation342623.37
Coefficient of variation (CV)4.3271694
Kurtosis55.885917
Mean79179.562
Median Absolute Deviation (MAD)882.5
Skewness6.9897988
Sum66510832
Variance1.1739078 × 1011
MonotonicityNot monotonic
2023-07-16T19:58:42.913635image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 112
 
13.3%
2 39
 
4.6%
1 19
 
2.3%
3 15
 
1.8%
4 14
 
1.7%
10 13
 
1.5%
5 9
 
1.1%
22 8
 
1.0%
13 8
 
1.0%
9 7
 
0.8%
Other values (539) 596
71.0%
ValueCountFrequency (%)
0 112
13.3%
1 19
 
2.3%
2 39
 
4.6%
3 15
 
1.8%
4 14
 
1.7%
5 9
 
1.1%
6 1
 
0.1%
7 6
 
0.7%
8 5
 
0.6%
9 7
 
0.8%
ValueCountFrequency (%)
3618689 1
0.1%
3535757 1
0.1%
3381049 1
0.1%
3259793 1
0.1%
2482266 1
0.1%
2337604 1
0.1%
2246313 1
0.1%
2176242 1
0.1%
2085815 1
0.1%
1894466 1
0.1%

Otros
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct314
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4898.2167
Minimum-1945
Maximum120464
Zeros455
Zeros (%)54.2%
Negative2
Negative (%)0.2%
Memory size6.7 KiB
2023-07-16T19:58:43.073669image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-1945
5-th percentile0
Q10
median0
Q35094
95-th percentile21789.6
Maximum120464
Range122409
Interquartile range (IQR)5094

Descriptive statistics

Standard deviation12102.988
Coefficient of variation (CV)2.4708969
Kurtosis42.893262
Mean4898.2167
Median Absolute Deviation (MAD)0
Skewness5.690676
Sum4114502
Variance1.4648233 × 108
MonotonicityNot monotonic
2023-07-16T19:58:43.256710image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 455
54.2%
2151 6
 
0.7%
1035 6
 
0.7%
6105 5
 
0.6%
268 3
 
0.4%
4641 3
 
0.4%
36917 3
 
0.4%
3719 3
 
0.4%
45 3
 
0.4%
6980 3
 
0.4%
Other values (304) 350
41.7%
ValueCountFrequency (%)
-1945 1
 
0.1%
-10 1
 
0.1%
0 455
54.2%
10 1
 
0.1%
20 2
 
0.2%
30 1
 
0.1%
45 3
 
0.4%
65 2
 
0.2%
168 1
 
0.1%
190 1
 
0.1%
ValueCountFrequency (%)
120464 1
0.1%
114182 1
0.1%
113357 1
0.1%
105818 1
0.1%
105607 1
0.1%
105477 1
0.1%
65849 1
0.1%
65821 1
0.1%
43573 1
0.1%
43438 1
0.1%

Total
Real number (ℝ)

HIGH CORRELATION 

Distinct834
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean343988.81
Minimum12406
Maximum4721668
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-07-16T19:58:43.407754image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum12406
5-th percentile25701.75
Q152328.25
median104333
Q3177579.75
95-th percentile1417583.7
Maximum4721668
Range4709262
Interquartile range (IQR)125251.5

Descriptive statistics

Standard deviation737336.59
Coefficient of variation (CV)2.1434901
Kurtosis14.711416
Mean343988.81
Median Absolute Deviation (MAD)56426
Skewness3.7617998
Sum2.889506 × 108
Variance5.4366524 × 1011
MonotonicityNot monotonic
2023-07-16T19:58:43.564782image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14029 3
 
0.4%
35710 3
 
0.4%
68538 2
 
0.2%
33772 2
 
0.2%
177477 1
 
0.1%
27032 1
 
0.1%
88854 1
 
0.1%
80197 1
 
0.1%
637473 1
 
0.1%
88093 1
 
0.1%
Other values (824) 824
98.1%
ValueCountFrequency (%)
12406 1
0.1%
12557 1
0.1%
12741 1
0.1%
13040 1
0.1%
13055 1
0.1%
13147 1
0.1%
13220 1
0.1%
13302 1
0.1%
13488 1
0.1%
13660 1
0.1%
ValueCountFrequency (%)
4721668 1
0.1%
4667183 1
0.1%
4555424 1
0.1%
4509157 1
0.1%
4251609 1
0.1%
4132351 1
0.1%
4060002 1
0.1%
4033261 1
0.1%
3971683 1
0.1%
3937277 1
0.1%

Total2
Real number (ℝ)

HIGH CORRELATION 

Distinct834
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean336184.93
Minimum12656
Maximum4667183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-07-16T19:58:43.720814image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum12656
5-th percentile26889.05
Q156000.25
median105095.5
Q3177889.5
95-th percentile1402587.6
Maximum4667183
Range4654527
Interquartile range (IQR)121889.25

Descriptive statistics

Standard deviation714290.17
Coefficient of variation (CV)2.1246942
Kurtosis15.316865
Mean336184.93
Median Absolute Deviation (MAD)55123
Skewness3.8188969
Sum2.8239534 × 108
Variance5.1021044 × 1011
MonotonicityNot monotonic
2023-07-16T19:58:43.869848image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38419 3
 
0.4%
14146 3
 
0.4%
41890 2
 
0.2%
115843 2
 
0.2%
96483 1
 
0.1%
90573 1
 
0.1%
83806 1
 
0.1%
611481 1
 
0.1%
88228 1
 
0.1%
178798 1
 
0.1%
Other values (824) 824
98.1%
ValueCountFrequency (%)
12656 1
0.1%
12912 1
0.1%
13072 1
0.1%
13127 1
0.1%
13139 1
0.1%
13237 1
0.1%
13346 1
0.1%
13428 1
0.1%
13605 1
0.1%
13777 1
0.1%
ValueCountFrequency (%)
4667183 1
0.1%
4609897 1
0.1%
4531772 1
0.1%
4509157 1
0.1%
4251609 1
0.1%
4132351 1
0.1%
4033261 1
0.1%
3870807 1
0.1%
3843534 1
0.1%
3777546 1
0.1%

Diferencia
Real number (ℝ)

ZEROS 

Distinct583
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7803.8786
Minimum-25884
Maximum665118
Zeros40
Zeros (%)4.8%
Negative622
Negative (%)74.0%
Memory size6.7 KiB
2023-07-16T19:58:44.180926image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-25884
5-th percentile-10145.7
Q1-4657.5
median-1071
Q30
95-th percentile42969.55
Maximum665118
Range691002
Interquartile range (IQR)4657.5

Descriptive statistics

Standard deviation53295.323
Coefficient of variation (CV)6.8293378
Kurtosis64.788984
Mean7803.8786
Median Absolute Deviation (MAD)2502
Skewness7.4015179
Sum6555258
Variance2.8403914 × 109
MonotonicityNot monotonic
2023-07-16T19:58:44.329952image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 40
 
4.8%
-513 6
 
0.7%
-423 6
 
0.7%
-2709 6
 
0.7%
999 5
 
0.6%
-3717 5
 
0.6%
-162 5
 
0.6%
-666 5
 
0.6%
-504 5
 
0.6%
-117 5
 
0.6%
Other values (573) 752
89.5%
ValueCountFrequency (%)
-25884 1
0.1%
-24579 1
0.1%
-24120 1
0.1%
-19278 1
0.1%
-19017 1
0.1%
-16920 1
0.1%
-16740 1
0.1%
-16677 1
0.1%
-16641 1
0.1%
-16587 1
0.1%
ValueCountFrequency (%)
665118 1
0.1%
563562 1
0.1%
471186 1
0.1%
419490 1
0.1%
407313 1
0.1%
406548 1
0.1%
372861 1
0.1%
301626 1
0.1%
269469 1
0.1%
247102 1
0.1%

Interactions

2023-07-16T19:58:37.747480image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:17.441923image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:19.186313image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:20.953248image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:22.877279image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:24.582332image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:26.169812image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:27.891197image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:29.594961image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:31.180023image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:32.838394image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:34.458757image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:36.188130image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:37.880508image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:17.587954image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:19.382356image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:21.117283image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:23.013310image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:24.719236image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:26.308845image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:28.020227image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:29.726990image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:31.323055image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:32.969425image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:34.591786image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:36.322160image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:38.021541image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:17.714984image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:19.500383image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:21.247311image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:23.139249image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:24.828246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:26.427871image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:28.138253image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:29.840015image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:31.446083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:33.090450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:34.700808image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:36.444188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:38.176575image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:17.854014image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:19.639416image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:21.382327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:23.290291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:24.957274image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:26.567904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:28.271283image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:29.973045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:31.579107image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:33.222481image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:34.824843image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:36.573216image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:38.308618image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:17.990054image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:19.788448image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:21.517358image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:23.427236image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:25.086228image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:26.719937image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:28.395312image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:30.107075image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:31.707130image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:33.355505image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:34.943866image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:36.698257image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:38.429647image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:18.119074image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:19.909474image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:21.645246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:23.555243image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:25.202228image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:26.855967image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:28.509345image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:30.219099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:31.827167image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:33.477538image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:35.077884image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:36.814272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:38.561672image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:18.262105image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:20.097516image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:21.782262image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:23.695229image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:25.336263image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:27.001001image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:28.636365image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:30.350129image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:31.967200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:33.614568image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:35.376952image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:36.939298image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:38.682701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:18.386132image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:20.220544image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:21.947114image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:23.829105image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:25.469310image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:27.129027image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:28.899423image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:30.457153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:32.093227image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:33.731592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:35.488988image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:37.049332image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:38.806718image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:18.526166image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:20.336570image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:22.066139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:23.946239image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:25.572679image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:27.256056image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:29.006447image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:30.566883image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:32.209241image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:33.847609image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:35.601012image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:37.161348image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:39.007761image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:18.671197image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:20.475116image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:22.207235image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:24.087214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:25.700709image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:27.395089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:29.130856image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:30.698915image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:32.343272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:33.979650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:35.727044image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:37.293390image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:39.136791image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:18.795226image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:20.604337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:22.339259image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:24.208243image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:25.824740image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:27.522116image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:29.248883image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:30.822944image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:32.465298image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:34.101664image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:35.845054image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:37.408404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:39.260818image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:18.932256image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:20.717244image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:22.627338image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:24.331277image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:25.936763image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:27.646146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:29.358908image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:30.942971image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:32.585338image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:34.219691image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:35.957094image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:37.517428image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:39.384863image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:19.039279image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:20.826266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:22.746362image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:24.453304image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:26.048785image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:27.766169image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:29.472933image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:31.056985image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:32.707368image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:34.332716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:36.070103image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-16T19:58:37.626465image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-07-16T19:58:44.467989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Añoid_Provincia<0.512 mbps0.512 - 1 Mbps1 - 6 Mbps6 - 10 Mbps10 - 20 Mbps20 - 30 Mbps>=30 MbpsOtrosTotalTotal2DiferenciaTrimestre
Año1.0000.000-0.088-0.325-0.1370.3370.4120.5820.7110.7350.3020.2980.0100.000
id_Provincia0.0001.000-0.256-0.248-0.187-0.255-0.326-0.273-0.2830.011-0.235-0.229-0.1710.000
<0.512 mbps-0.088-0.2561.0000.3910.4330.2990.2610.2480.2150.0590.4100.427-0.0920.000
0.512 - 1 Mbps-0.325-0.2480.3911.0000.4100.3320.2720.1190.039-0.1630.3110.324-0.0220.000
1 - 6 Mbps-0.137-0.1870.4330.4101.0000.4520.4200.2870.326-0.0240.7630.7660.1760.000
6 - 10 Mbps0.337-0.2550.2990.3320.4521.0000.7500.6540.6610.2940.7300.7340.1490.000
10 - 20 Mbps0.412-0.3260.2610.2720.4200.7501.0000.7420.7730.3400.7380.7430.1640.000
20 - 30 Mbps0.582-0.2730.2480.1190.2870.6540.7421.0000.7930.5170.6680.6660.1170.000
>=30 Mbps0.711-0.2830.2150.0390.3260.6610.7730.7931.0000.5770.7250.7190.2030.000
Otros0.7350.0110.059-0.163-0.0240.2940.3400.5170.5771.0000.3400.3390.0100.000
Total0.302-0.2350.4100.3110.7630.7300.7380.6680.7250.3401.0000.9940.2550.000
Total20.298-0.2290.4270.3240.7660.7340.7430.6660.7190.3390.9941.0000.1780.000
Diferencia0.010-0.171-0.092-0.0220.1760.1490.1640.1170.2030.0100.2550.1781.0000.000
Trimestre0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-07-16T19:58:39.565886image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-07-16T19:58:39.813940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

AñoTrimestreid_Provincia<0.512 mbps0.512 - 1 Mbps1 - 6 Mbps6 - 10 Mbps10 - 20 Mbps20 - 30 Mbps>=30 MbpsOtrosTotalTotal2Diferencia
020223029985277092903152979152670441241936186896582147216684609897111771
12022315170574234371678295194628692125310510547715476791552332-4653
2202232710384031075389509937375029822087029374388-4095
3202233461098701678218938804915828793903711144146157178-13032
4202234109014444570730943468215309175632002416577813891326865
52022359901131215332411161570989271126503441387310386681039559-891
620223667038652342723948777621706569507107144846145449-603
7202237107055494721046855182633202110219516759268959269922-963
820223897030702353819545619456401770458906853882551-14013
920223958018791913515254360835190458950118823124016-5193
AñoTrimestreid_Provincia<0.512 mbps0.512 - 1 Mbps1 - 6 Mbps6 - 10 Mbps10 - 20 Mbps20 - 30 Mbps>=30 MbpsOtrosTotalTotal2Diferencia
830201411441339870771488401582202208395893615-9657
83120141154674618843047301062108094736911993537
83220141165301967764061719231400009129794600-3303
833201411753102051056000005158956386-4797
83420141187030125440100201255712656-99
8352014119161016252497210100002676028227-1467
836201412084561244683452252032868452306680506013506220-207
837201412112341053122817242210900003711338094-981
83820141221206070309026000003152737152-5625
83920141236034672832101177936203000130032133371-3339